🚀 Available for Internships

Jaya Sabari R

Software Developer  ·  Portfolio

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Frontend Developer Python Developer Machine Learning Enthusiast
💻 VS Code ☕ Eclipse 📓 Jupyter Notebook

Computer Science Engineering student focused on Cybersecurity, Machine Learning, and Full-Stack Development. Passionate about building intelligent, scalable, and real-world impactful systems.

Turning data into decisions Turning ideas into applications Turning problems into solutions
Jaya Sabari
about me

Who I Am

I'm Jaya Sabari R, a Computer Science Engineering student from Chennai, Tamil Nadu, with strong foundations in software development and machine learning.

I co-authored a research paper on Crime Arrest Prediction using Stacking Ensemble Learning, combining Random Forest, XGBoost, and MLP Neural Networks to achieve 96% accuracy on real-world crime data.

I enjoy solving complex problems using data-driven approaches and writing clean, maintainable code. My long-term goal is to integrate Software Engineering + AI + Cybersecurity to develop intelligent systems that create real-world impact.

Currently Exploring

  • ⚛React.js — Frontend Development
  • 🍃MongoDB — Database Systems
  • 🔐Cybersecurity Concepts
  • 🤖Advanced Machine Learning Techniques
Location
Chennai, Tamil Nadu, India
Date of Birth
05 September 2005
Degree
B.E Computer Science Engineering
Research Area
Machine Learning & Cybersecurity
CGPA
8.3 / 10.0
technical skills

What I Know

💻Programming Languages
☕ Java80%
🐍 Python88%
🗄 SQL75%
C70%
🌐Web Development
HTML590%
CSS385%
JavaScript72%
React.js Learning40%
MongoDB Basics35%
📊Machine Learning & Data
scikit-learn85%
XGBoost82%
Random Forest / MLP80%
pandas & NumPy83%
Streamlit75%
🧰Tools & Platforms
VS Code92%
Git & GitHub78%
Google Colab / Jupyter88%
Eclipse75%
Kaggle80%
work experience

Internships

🏢 Corizo
Aug 2024 – Sep 2024
Cybersecurity Intern  ·  Online
  • Completed a cybersecurity internship focused on system security, threat analysis, and secure application practices.
  • Analyzed common web and network vulnerabilities including SQL injection, XSS, and authentication flaws.
  • Performed basic vulnerability assessment and security testing on sample applications.
  • Applied cybersecurity best practices such as secure coding, access control, and data protection techniques.
  • Documented findings and security recommendations following standard cybersecurity reporting practices.
research & projects

What I Built

🧠 Crime Arrest Prediction Using Stacking Ensemble Learning
📄 Research Paper
Panimalar Engineering College  ·  Authors: Deepa P, Jayasanjay T, Jaya Sabari R
📌 Project Overview

Developed an advanced Stacking Ensemble ML Model to predict the probability of arrest in criminal cases using real-world crime datasets. Combines multiple ML algorithms for superior predictive performance.

🔍 Methodology
Base Model 1Random Forest Classifier
Base Model 2XGBoost Classifier
Meta LearnerMLP Neural Network
DatasetChicago Crime Dataset (Kaggle)
PreprocessingMedian Imputation · One-Hot Encoding · Scaling
📈 Results
96%
✅ Accuracy
0.96
📊 Precision
0.96
🎯 Recall
0.96
⚡ F1 Score
0.99
🏆 ROC-AUC
🛠 Technologies
Pythonscikit-learnXGBoost Random ForestMLP Neural Network pandasStreamlitKaggle Dataset
📊 Prediction Insights
Low Arrest Probability
Low Arrest Probability — 5.03%
💡 Key Learnings
Ensemble LearningModel Evaluation Metrics Real-world Data CleaningDeployment with Streamlit
📊 Crime Rate Prediction Using ML
🐍 Python Project
Python · scikit-learn · Flask · Gradio  ·  2025
📌 Overview

Crime rate prediction system using stacking ensemble learning to classify crime cases as Closed or Open. Built an interactive web dashboard for crime trend visualization and real-time case status prediction.

✨ Highlights
  • Performed data preprocessing and feature engineering on large-scale Indian crime datasets.
  • Implemented stacking ensemble combining Random Forest, SVM, KNN, and Logistic Regression.
  • Built interactive web dashboard using Flask and Gradio for crime trend visualization.
🛠 Technologies
Pythonscikit-learnPandasFlaskGradio
🎮 Random Puzzle Game
🏢 Python CLI Project
📌 Overview

A logic-based Python puzzle game with interactive challenges and score tracking. Focused on clean code structure and seamless CLI user experience.

✨ Highlights
  • Implemented logic-based challenges with dynamic puzzle generation.
  • Built user input validation and real-time score tracking.
  • Focused on clean code structure and user experience.
🛠 Technologies
PythonLogic DesignCLI
certifications & training

Achievements

☁️
AWS Cloud Practitioner Essentials
AWS Training & Certification
May 27, 2024  ·  Click to view
☕
Programming in Java — Elite
NPTEL · IIT Kharagpur · Skill India
Jul–Oct 2024  ·  Score: 60%  ·  Click to view
🔐
Cybersecurity Internship
Corizo  ·  Wipro DICE ID: CRZ65692
Aug–Sep 2024  ·  Click to view
🤖
Automation Developer Associate Training
UiPath Academy  ·  Signed by Daniel Dines
22 Feb 2026  ·  Click to view
education

My Journey

2023 — 2027
B.E Computer Science Engineering
Panimalar Engineering College, Chennai
⭐ CGPA: 8.3 / 10.0
2022 — 2023
Higher Secondary (Class XII)
Tamil Nadu State Board
📊 Percentage: 87%
contact

Get In Touch

Email
jayasabariimmi@gmail.com
Phone
+91-8220760571
LinkedIn
jaya-sabari-r
GitHub
Jaya-sabari-immi